Computational and Systems Biology of Molecules, Pathways, and Processes
Computational biology research at Memorial Sloan-Kettering Cancer Center aims to analyze and simulate biological processes at different levels of organization, predict the results of interventions in biological systems, and improve the prevention, diagnosis, prognosis, and therapy of cancer. Close collaboration with experimental and clinical groups using high-throughput and functional genomics data is essential to the achievement of these goals. Computational biology can help interpret detailed molecular profiles of cancerous and noncancerous cells, molecular response profiles of therapeutic agents, and a person's genetic profile to assist in the development of better diagnostics and prognostics, as well as improved therapies. Intelligent use of computational methods using detailed molecular and genomic data can lead us to discoveries in cancer biology, and reduce the trial and error of drug development.
Sander Group - Research in Computational and Systems Biology
Current areas of research in the Sander group include: identification of oncogenically altered pathways from genomic and molecular profiling in cancer, algorithms for the analysis of cancer genomics data, design of combinatorial cancer therapy, drug target identification, knowledge representation of biological pathways, protein evolution, specificity in protein networks, and the function of small RNAs.